A low-voltage power distribution cabinet

Abstract

The application discloses a low-voltage power distribution cabinet, and relates to the technical field of low-voltage power distribution cabinets, which comprises a cabinet body, a cabinet door hingedly connected to the cabinet body and a plurality of electrical elements installed in the cabinet body, a processing module is arranged on the cabinet door, a detection module is installed on the top surface in the cabinet body, a fire extinguishing module is installed on the top surface in the cabinet body, and an alarm module comprises an audible and visual alarm installed on the top surface in the cabinet body; the processing module, the alarm module, the detection module and the fire extinguishing module are used in cooperation, so that the situation in the low-voltage power distribution cabinet can be monitored in real time, fire or other faults in the low-voltage power distribution cabinet can be avoided, and the use of the low-voltage power distribution cabinet is facilitated; the processing module is used for weighted calculation of four dangerous levels, a device health degree is obtained, a weight coefficient is dynamically adjusted in combination with historical fault data, and a device state is converted into a quantifiable health index; when a JK value is lower than a threshold value, a replacement warning is generated in advance instead of waiting for a fault to occur.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of low-voltage power distribution cabinets, in particular to a low-voltage power distribution cabinet. BACKGROUND

[0002] In the power system, as a key device for power distribution, the low-voltage power distribution cabinet is widely used in various scenes such as industry, commerce and residence, and plays an important role in power distribution, control and protection. However, due to the dense electrical components in the power distribution cabinet, safety hazards are easily caused by factors such as line aging, poor contact, and excessive load during long-term operation;

[0003] The existing low-voltage power distribution cabinet has the following problems when in use:

[0004] On the one hand, the fault detection method is lagging behind; most power distribution cabinets rely on manual regular inspection to find abnormalities and cannot monitor internal temperature, smoke and other key parameters in real time; when electrical components cause insulation layer aging or short circuit due to overheating, it is often difficult to give timely warning, leading to the escalation of faults and even causing a fire; and when monitoring parameters, most of them give warnings when abnormalities occur, or give early warnings, and there is no clear understanding of the aging process of the equipment, so that the power distribution cabinet may cause dangerous situations during use due to equipment aging;

[0005] On the other hand, the fire prevention and control capability is insufficient; the traditional power distribution cabinet lacks automatic fire extinguishing devices, and once a fire occurs, the fire is easy to spread rapidly, which not only causes equipment damage and power interruption, but also endangers personnel safety and causes significant economic losses;

[0006] With the advancement of intelligent power grid construction, higher requirements are put forward for the safety, reliability and intelligent level of low-voltage power distribution cabinets; how to realize real-time monitoring of the internal state of the power distribution cabinet, early warning and automatic disposal of faults has become a problem to be solved in the industry; therefore, developing a low-voltage power distribution cabinet with real-time detection, intelligent alarm and automatic fire extinguishing function has important practical significance for improving the stability of power system operation, reducing operation and maintenance cost, and ensuring personnel and equipment safety. SUMMARY

[0007] The present application relates to the technical field of low-voltage power distribution cabinets, in particular to a low-voltage power distribution cabinet.

[0008] In order to achieve the above purpose, the present application adopts the following technical scheme:

[0009] A low-voltage power distribution cabinet, comprising a cabinet body, a cabinet door hinged to the cabinet body, and a plurality of electrical components installed in the cabinet body, the cabinet door is provided with a processing module;

[0010] The processing module receives the data transmitted by the detection module, analyzes the transmitted image data, determines the number of changes required to reach the explosion point at the abnormal position through estimation, compares the number of changes with the threshold value to obtain the corresponding danger level; through the analysis of the gray value change of the gray processed image, the corresponding danger level is obtained again; the temperature data and gas concentration data transmitted are analyzed, the time required to reach the corresponding threshold value is judged according to the change rate of temperature and gas concentration, and the corresponding danger level is calculated; the equipment health degree of the cabinet body is obtained through the weighted calculation of the four danger levels, if the equipment health degree is less than the corresponding threshold value, a replacement warning signal is generated, and the replacement warning signal is transmitted to the alarm module;

[0011] The detection module is installed on the top surface of the cabinet body.

[0012] The fire extinguishing module is installed on the top surface of the cabinet body.

[0013] The alarm module includes an audible and visual alarm installed on the top surface of the cabinet body.

[0014] Preferably, the detection module includes a camera, a temperature sensor and a smoke sensor.

[0015] Preferably, the fire extinguishing module includes a fire extinguisher.

[0016] Preferably, the processing module includes a processor and a controller, and the processor is electrically connected between the camera, the temperature sensor and the smoke sensor, and the controller is electrically connected between the audible and visual alarm and the fire extinguisher.

[0017] Preferably, the cabinet body is internally provided with an intelligent detection assembly, which includes a detection module, a processing module and an alarm module.

[0018] The detection module detects the image data, temperature data and gas concentration data inside the power distribution cabinet, and transmits the detected data to the processing module.

[0019] The alarm module receives the replacement warning signal transmitted by the processing module, then controls the warning light to issue an audible and visual alarm, and sends information to the staff through the transmission function of the module to remind the staff to replace the power distribution cabinet.

[0020] Preferably, the processing module analyzes the image data as follows:

[0021] S1: According to the rotation angle between the camera and the initial direction, the corresponding preset gray contrast chart of the camera shooting position is determined.

[0022] S2: Perform grayscale processing on the image data at corresponding time points according to a set time interval, divide the grayscale processed image data into pixel blocks, calculate the grayscale value of each segmented grayscale image block, and then input the calculated grayscale value data of the grayscale image blocks. Compare the grayscale values ​​at the corresponding positions on the corresponding preset grayscale image. If the absolute value of the difference between the two grayscale values ​​exceeds the preset difference threshold of the grayscale comparison image, then the corresponding position of the grayscale image block is determined to be an abnormal position.

[0023] S3: If adjacent pixel blocks at an abnormal location are also at abnormal locations, then they are determined to be at the same abnormal location, and the area of ​​that abnormal location is... The number of grayscale image patches at the abnormal location is multiplied by the area of ​​a single grayscale image patch. Then, the frequency of changes at the abnormal location is analyzed and marked. The preset abnormal area threshold is used; if Then, the total number of abnormal locations in the detected image data. If statistics are performed, Then, the frequency of changes at the abnormal location is analyzed and marked. This is a preset proportional coefficient. To detect the total number of grayscale image blocks in the image data summary;

[0024] S4: Retrieve historical data, and compare the grayscale image blocks at the corresponding abnormal locations with normal grayscale values. And grayscale data corresponding to the critical point of dangerous outbreak. Acquire; measure the change in grayscale value of grayscale image blocks at corresponding normal locations within adjacent acquisition time periods. Record the changes and calculate the threshold number of changes based on the amount of grayscale value change. The grayscale value data of the detected grayscale image block at the marked position of the change count analysis is compared with the grayscale value data at the corresponding position on the corresponding preset grayscale comparison map. By comparing the results, the predicted number of changes corresponding to the detected grayscale image patches can be obtained. ,like If so, it is determined that there is a danger at the detection location, and the danger level is... , This is a preset proportional coefficient;

[0025] S5: Change in grayscale value at adjacent detection time points at the detection location To acquire the value, if the preset grayscale value at the corresponding location changes by a threshold value... If so, it is determined that there is a danger at the detection location, and the danger level is... .

[0026] Preferably, the processing module performs the analysis steps of temperature and gas concentration data as follows:

[0027] K1: Establish a binary coordinate system with temperature data / gas concentration data and collection time, draw corresponding coordinate points in the coordinate system, and connect adjacent coordinate points. Calculate the slope of the connecting line, and compare the slopes of the temperature connecting line and the gas concentration connecting line with the corresponding preset change threshold value;

[0028] K2: If the slope of the corresponding connecting line is greater than the preset change threshold value of the corresponding item, it is determined that there is a danger, and the danger level and is equal to the slope value of the corresponding item minus the preset change threshold value of the corresponding item, and divided by the preset change threshold value of the corresponding item;

[0029] K3: If the slope of the corresponding connecting line is less than the preset change threshold value of the corresponding item, record the detection data of the current corresponding item, and substitute the detection data before the time point into the formula , get and specific numerical value, is the detection data of the corresponding item, is the detection time; then according to the formula, it can be judged that after the time , the detection data of the corresponding item will reach the preset warning threshold value, if the preset reaction time , it is determined that there is a danger, and the danger level and is equal to the time of the corresponding item minus the preset reaction time of the corresponding item, and divided by the preset reaction time of the corresponding item.

[0030] Preferably, the processing module performs the analysis steps of equipment health degree as follows:

[0031] M1: Quantify the equipment health degree of the power distribution cabinet according to the danger level, and the equipment health degree , , , , and are the weight coefficients of the corresponding items respectively; when the equipment health degree is less than the preset equipment health degree threshold value, it is determined that the safety hidden danger of the equipment continues to use is larger, a replacement warning signal is generated, and the replacement warning signal is transmitted to the alarm module;

[0032] M2: Retrieve historical failure information, count the occurrence times of the three kinds of abnormalities in the historical failure information, and then divide the corresponding occurrence times of the three kinds of abnormalities by the total number of occurrences of the three kinds of abnormalities to get the corresponding weight coefficients 、 and ;

[0033] M3: the accuracy of the two analysis methods of the number of changes and the change of the gray value is obtained, the accuracy corresponding to the analysis method is divided by the sum of the accuracy of the two analysis methods, and the corresponding weight coefficient is obtained and .

[0034] In summary, due to the adoption of the above technical scheme, the beneficial effects of the present application are:

[0035] 1. Through the mutual cooperation of the processing module, the alarm module, the detection module and the fire extinguishing module, the situation in the low-voltage power distribution cabinet can be monitored in real time, and the occurrence of fire or other faults in the low-voltage power distribution cabinet can be avoided, thereby facilitating the use of the low-voltage power distribution cabinet.

[0036] 2. The weighted calculation of the four dangerous levels is obtained by the processing module, the equipment health degree is obtained, the weight coefficient is dynamically adjusted combined with the historical fault data, and the equipment state is converted into a quantifiable health index; when the JK value is lower than the threshold value, a replacement warning is generated in advance, instead of waiting for the occurrence of a fault. BRIEF DESCRIPTION OF DRAWINGS

[0037] Fig. 1 A front view structure schematic diagram provided by the embodiment of the present application is shown;

[0038] Fig. 2 A cabinet structure schematic diagram provided by the embodiment of the present application is shown;

[0039] Fig. 3 A system flowchart provided by the embodiment of the present application is shown.

[0040] LEGEND:

[0041] 1. Cabinet; 2. Electrical element; 3. Processing module; 4. Cabinet door; 5. Fire extinguishing module; 6. Detection module; 7. Alarm module. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0043] Please refer to Figs. 1-3 , the present application provides a technical scheme:

[0044] A low-voltage power distribution cabinet comprises a cabinet body 1, a cabinet door 4 hinged to the cabinet body 1, and a plurality of electrical elements 2 installed in the cabinet body 1, and a processing module 3 is arranged on the cabinet door 4;

[0045] A detection module 6 is arranged in the middle of the top surface of the cabinet body 1, and the detection module 6 comprises a camera, a temperature sensor and a smoke sensor, which are used to collect information in the low-voltage power distribution cabinet, and the processing module 3 is used to determine whether the low-voltage power distribution cabinet is faulty, so that the fault of the low-voltage power distribution cabinet can be handled in time;

[0046] A fire extinguishing module 5 is arranged on the top surface of the cabinet body 1, and the fire extinguishing module 5 comprises a fire extinguisher, which is used to extinguish fire in the low-voltage power distribution cabinet, so that the occurrence of fire can be avoided, thereby reducing the loss.

[0047] An alarm module 7 comprises an audible and visual alarm arranged on the top surface of the cabinet body 1, which is used to remind the staff that the low-voltage power distribution cabinet is faulty, so that the staff can handle the fault of the low-voltage power distribution cabinet in time, the occurrence of fire can be avoided, and the use of the low-voltage power distribution cabinet is facilitated.

[0048] In the application, the processing module 3 comprises a processor and a controller, the processor is electrically connected with the camera, the temperature sensor and the smoke sensor, and the controller is electrically connected with the audible and visual alarm and the fire extinguisher; through the cooperation of the processing module 3, the alarm module 7, the detection module 6 and the fire extinguishing module 5, the situation in the low-voltage power distribution cabinet can be monitored in real time, the occurrence of fire or other faults in the low-voltage power distribution cabinet can be avoided, and the use of the low-voltage power distribution cabinet is facilitated.

[0049] The cabinet body 1 is internally provided with an intelligent detection assembly, and the intelligent detection assembly comprises the detection module 6, the processing module 3 and the alarm module 7;

[0050] The detection module 6 detects image data, temperature data and gas concentration data in the power distribution cabinet and transmits the detected data to the processing module 3;

[0051] The processing module 3 receives the data transmitted by the detection module 6, analyzes the transmitted image data, estimates the number of changes required to reach the burst point at the abnormal position, compares the number of changes with a threshold value to obtain a corresponding danger level, analyzes the change amount of the gray value of the image after gray processing to obtain a corresponding danger level again, analyzes the transmitted temperature data and gas concentration data, judges the time required to reach a corresponding threshold value according to the change rate of the temperature and the gas concentration, and calculates a corresponding danger level; the equipment health degree of the cabinet body 1 is obtained through weighted calculation of the four danger levels, if the equipment health degree is less than a corresponding threshold value, a replacement warning signal is generated and transmitted to the alarm module 7;

[0052] The system monitors the external images of various devices inside the power distribution cabinet using a camera. Based on the rotation angle between the camera and a predetermined initial direction, it determines the preset grayscale comparison image corresponding to the camera's shooting position. The image data at corresponding time points are processed in grayscale at set time intervals. The processed image data is then segmented according to pixel size, and the grayscale value of each segmented grayscale image block is calculated. Compare the grayscale values ​​at the corresponding positions on the corresponding preset grayscale image. If the absolute value of the difference between the two grayscale values ​​exceeds the preset difference threshold of the grayscale comparison image, then the corresponding position of the grayscale image block is determined to be an abnormal position.

[0053] The matching mechanism between the camera rotation angle and the preset grayscale comparison image is based on the principle of spatial mapping. Specifically, the system pre-processes the normal cabinet interior images taken by the camera at different rotation angles (such as 0°, 30°, and 60°) to generate standard grayscale maps corresponding to each angle. During actual detection, the system obtains the current camera angle through the encoder and automatically calls the corresponding grayscale comparison image. Grayscale processing typically uses a weighted average method (such as the RGB to grayscale formula: Gray=0.299R+0.587G+0.114B) to convert the color image into an 8-bit grayscale image (0-255 levels), and then divides it into 16×16 pixel blocks to facilitate the calculation of the average grayscale value of each block. The setting of the preset difference threshold needs to be combined with the material characteristics of the components. For example, the normal grayscale value of copper busbar is 180-200, and the grayscale value drops to below 150 after oxidation. Therefore, the threshold can be set to 30 (i.e., (≥30 is considered abnormal).

[0054] If adjacent pixel blocks at an abnormal location are also at abnormal locations, they are determined to be at the same abnormal location, and the area of ​​that abnormal location is... The number of grayscale image patches at the abnormal location is multiplied by the area of ​​a single grayscale image patch. Then, the frequency of changes at the abnormal location is analyzed and marked. The preset abnormal area threshold is used; if Then, the total number of abnormal locations in the detected image data. If statistics are performed, Then, the frequency of changes at the abnormal location is analyzed and marked. This is a preset proportional coefficient. To detect the total number of grayscale image blocks in the image data summary;

[0055] Abnormal area threshold The settings need to take into account the component size. For example, if the abnormal contact area of ​​a small relay exceeds 100mm², it may affect the contact performance. Set to 100 mm2; when the abnormal area is small (such as <100 mm2), if the number of abnormal points exceeds 5% of the total pixel block number (such as >5% of the total pixel block number), it indicates that there is a risk of multi-point aging, and needs to be marked for analysis;

[0056] The historical data is called, the gray image block at the abnormal position is obtained corresponding to the normal gray value data , and the gray value data corresponding to the critical point of the dangerous explosion is obtained; the gray value change amount of the gray image block corresponding to the normal position in the adjacent collection time period is recorded , and the change frequency threshold is calculated based on the gray value change amount ; the detection gray value data of the gray image block at the marked position is compared with the gray value data at the corresponding position on the preset gray comparison chart , to obtain the expected change frequency of the detection gray image block , if , it is determined that there is a danger at the detection position, and the danger level , is a preset proportion coefficient;

[0057] The gray value of the critical point of the dangerous explosion is determined through an accelerated aging experiment, for example, the gray value of a circuit breaker contact decreases from normal 180 to 120, and a spark appears, so ; is the average gray value during normal operation (such as 180); the gray change amount of the adjacent collection time period is usually the average change value within 1 hour, if the gray unit, then (120-180) / 5=-12 times (the negative sign indicates a decreasing trend of gray); when a certain area 160, 180 is detected, then (160-180) / 5=-4 times, if , then -6 times, because -4>-6, it is determined that there is a danger, (-4-(-6)) / (-6)=0.33 (normalized danger level);

[0058] The gray value change amount of the adjacent detection time point at the detection position is obtained, if the preset gray value change threshold at the corresponding position , then it is also determined that there is a danger at the detection position, and the danger level .

[0059] ​​The data detected by the temperature sensor and the smoke sensor are acquired, and a binary coordinate system is established with temperature data / gas concentration data and collection time. Corresponding coordinate points are plotted in the coordinate system, and lines are drawn between adjacent coordinate points. The slope of the line is calculated, and the slope of the temperature line and the slope of the gas concentration line are compared with the preset change threshold of the corresponding item. If the slope of the corresponding line is greater than the preset change threshold of the corresponding item, it is determined that there is a danger, and the danger level and is equal to the slope value of the corresponding item minus the preset change threshold of the corresponding item, and divided by the preset change threshold of the corresponding item.

[0060] If the slope of the corresponding line is less than the preset change threshold of the corresponding item, the detection data of the current corresponding item is recorded, and the detection data before the time point is substituted into the formula , to obtain and the specific value of is the detection data of the corresponding item, is the detection time; then according to the formula, it can be judged that after the time , the detection data of the corresponding item will reach the preset warning threshold, if the preset reaction time , it is determined that there is a danger, and the danger level and is equal to the time of the corresponding item minus the preset reaction time of the corresponding item, and divided by the preset reaction time of the corresponding item.

[0061] The temperature data collection interval is usually 5 minutes to draw a temperature-time curve; the slope calculation uses two-point difference method, such as the temperature at time =25℃, minutes 26℃, the slope (26-25) / 5=0.2℃ / min; the preset change threshold is set according to the element temperature rise limit value, for example, the contactor allows the temperature rise rate to be 0.5℃ / min, so the threshold is set to 0.5; when 0.6>0.5, (0.6-0.5) / 0.5=0.2, i.e. the danger level is 20%;

[0062] When the slope is less than the threshold, the historical data (such as the past 10 time points) is fitted by linear regression, for example, the temperature data of a certain area is fitted as 0.1t+20, and the preset warning threshold is 40℃, then the threshold time (40-20) / 0.1=200 minutes; if preset reaction time 120 minutes, since 200≤120 is not true, determine no danger; if after fitting 100 minutes≤120 minutes, then (100-120) / 120=-0.17 (negative value indicates insufficient remaining time, danger level 17%);

[0063] According to the danger level, the equipment health degree of the power distribution cabinet is quantified, and the equipment health degree , , , , and are the weight coefficients of the corresponding items respectively; when the equipment health degree is less than the preset equipment health degree threshold, it is determined that the safety risk of continuing to use the equipment is large, a replacement warning signal is generated, and the replacement warning signal is transmitted to the alarm module 7;

[0064] Health degree formula , the weight coefficient needs to be set according to the equipment operation characteristics; taking an industrial power distribution cabinet as an example, historical data shows that 60% of the failures are caused by element appearance abnormalities (such as oxidation, cracks), 30% are caused by temperature abnormalities, and 10% are caused by smoke concentration abnormalities, so 0.6, 0.3, 0.1; and correspond to the accuracy weights of "change times" and "gray value change" in image analysis respectively, if the test shows that the change times method has an accuracy of 85% and the gray change method has an accuracy of 75%, then 85 / (85+75)=0.53, 0.47;

[0065] Danger level needs to be normalized to the [0, 1] interval, for example 0.33 (example in the foregoing), 0.2 (when 30, 25, (30-25) / 25=0.2), 0.2, 0 (no abnormality in gas concentration), then 0.221; if the preset health degree threshold is 0.6, since 0.221<0.6, a replacement warning is generated;

[0066] The historical fault information is called, the occurrence times of three kinds of abnormalities in the historical fault information are counted, and then the corresponding occurrence times of the three kinds of abnormalities are divided by the total number of occurrences of the three kinds of abnormalities to obtain the corresponding weight coefficient , and ; the accuracy of the two analysis methods of change number and gray value change for abnormality judgment is obtained, and the accuracy of the corresponding analysis method is divided by the sum of the accuracies of the two analysis methods to obtain the corresponding weight coefficient and ;

[0067] If a power distribution cabinet occurs 10 times of failure within 1 year, 6 times of which are temperature abnormalities, 3 times of which are image abnormalities, and 1 time of which is smoke abnormality, then 3 / 10=0.3, 6 / 10=0.6, 1 / 10=0.1, i.e. the weight of the temperature parameter is increased; the accuracy of the two image analysis methods is verified regularly, for example, 100 known fault samples are selected, 85 times are correctly identified by the change number method, and 75 times are correctly identified by the gray value change method, so 85 / (85+75)=0.53, 0.47. When the device aging causes the appearance change of the element to be more significant, the analysis accuracy can be improved by increasing ;

[0068] The alarm module 7 receives the replacement warning signal transmitted by the processing module 3, then controls the warning light to issue sound and light alarm, and sends information to the staff through the transmission function of the module to remind the staff to replace the power distribution cabinet.

[0069] The detection module 6 collects data in real time and transmits them to the processing module 3, and the processing module 3 calculates the health degree every 10 minutes ; when <0.6, a first level early warning (such as APP push) is triggered; if <0.4, it is determined as an emergency failure, and a sound and light alarm (such as a 80dB sound of a buzzer + a red light flashing) is started, and a message (including the fault position, the health degree value, and the recommended processing time) is sent to the operation and maintenance personnel through the 4G module. For example, the health degree of a certain cabinet 1 is 0.35 <0.4, the system generates a warning information "the health degree of the contactor C1 is insufficient, and it is recommended to replace within 24 hours", and the camera is focused on the element to provide real-time video for remote diagnosis;

[0070] The fire extinguishing module 5 is automatically started when the smoke concentration is greater than 1% obs / m and the temperature is greater than 100℃, and is also associated with the health degree: when <0.3 and temperature > 80℃, even if no smoke is detected, it is determined that there is a high risk of fire hazard, and the fire extinguisher is started to spray dry powder (such as 5kg ABC dry powder, covering an area of 5m²) in advance to prevent the failure from escalating. For example, a certain area component causes the temperature to rise to 85℃ due to poor contact, and the health degree 0.28 < 0.3, the system automatically starts the fire extinguishing module 5 and cuts off the power supply of the circuit.

[0071] Working principle: when the low-voltage power distribution cabinet catches fire, the camera captures the image and transmits it to the processor, which controls the fire extinguisher to start and then spray dry powder through the controller, which covers the ignition point and isolates oxygen to achieve the purpose of fire extinguishing; and the sound and light alarm will light up and make a sound to remind the staff that this low-voltage power distribution cabinet has failed, so as to facilitate timely fault handling of the low-voltage power distribution cabinet.

[0072] The above description of the embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A low voltage switchgear cabinet comprising a cabinet body (1), a cabinet door (4) hinged to the cabinet body (1) and a plurality of electrical components (2) mounted within the cabinet body (1), characterized in that, The cabinet door (4) is provided with a processing module (3); The processing module (3) receives the data transmitted by the detection module (6), analyzes the transmitted image data, determines the number of changes required to reach the burst point at the abnormal position through estimation, compares it with the change threshold to obtain the corresponding danger level, analyzes the gray value change of the gray processed image, and obtains the corresponding danger level again; the temperature data and gas concentration data transmitted are analyzed, the time required to reach the corresponding threshold is judged according to the temperature and gas concentration change rate, and the corresponding danger level is calculated; the equipment health degree of the cabinet (1) is obtained by weighted calculation of the four danger levels, if the equipment health degree is less than the corresponding threshold, a replacement warning signal is generated, and the replacement warning signal is transmitted to the alarm module (7); The steps of image data analysis of the processing module (3) are as follows: S1: According to the rotation angle between the camera and the initial direction, the corresponding preset gray contrast of the camera shooting position is determined; S2: grayscale processing the image data of the corresponding time point according to a set time interval, and segmenting the grayscale processed image data according to the size of the pixel block, calculating the grayscale value of the segmented grayscale image block, and comparing the calculated grayscale value data of the grayscale image block with the grayscale value data of the corresponding position on the preset grayscale contrast graph If the absolute value of the difference between the two grayscale values exceeds the preset difference threshold value of the grayscale contrast graph, it is determined that the corresponding position of the grayscale image block is an abnormal position.​ S3: If the adjacent pixel block of the abnormal position is also an abnormal position, it is determined as the same abnormal position, and the area of the abnormal position is the number of abnormal position gray image blocks multiplied by the area of a single gray image block, and if , the number of changes analysis mark is performed on the abnormal position, is a preset abnormal area threshold; if , the total number of abnormal positions in the detection image data is counted, and if , the number of changes analysis mark is performed on the abnormal position, is a preset proportion coefficient, is the total number of detection image data summary gray image blocks; S4: retrieve historical data, corresponding to the abnormal position at the gray image block in the normal gray value data , and the gray value data corresponding to the critical point of the dangerous outbreak ; get; record the gray value change amount of the gray image block corresponding to the normal position in the adjacent collection time period ; calculate the change frequency threshold based on the gray value change amount ; compare the detected gray value data of the gray image block at the change frequency analysis mark position with the gray value data at the corresponding position on the corresponding preset gray comparison chart , get the expected change frequency corresponding to the detected gray image block , if , then determine that there is a danger at the detection position, and the danger level , is a preset proportion coefficient; S5: the gray value change amount of the adjacent detection time point at the detection position If the preset gray value change threshold at the corresponding position is acquired , it is also determined that there is a danger at the detection position, and the danger level ; The detection module (6) is installed on the top surface of the cabinet (1); The fire extinguishing module (5) is installed on the top surface of the cabinet (1); The alarm module (7) includes a sound and light alarm installed on the top surface of the cabinet (1).

2. A low voltage switchgear according to claim 1, characterized in that The detection module (6) includes a camera, a temperature sensor and a smoke sensor.

3. A low voltage switchgear according to claim 2, characterized in that The fire extinguishing module (5) includes a fire extinguisher.

4. A low voltage switchgear according to claim 3, characterized in that The processing module (3) includes a processor and a controller, and the processor is electrically connected with the camera, the temperature sensor and the smoke sensor, and the controller is electrically connected with the sound and light alarm and the fire extinguisher.

5. A low voltage switchgear according to claim 1, characterized in that The cabinet (1) is provided with a smart detection assembly, which includes a detection module (6), a processing module (3) and an alarm module (7); The detection module (6) detects the image data, temperature data and gas concentration data in the power distribution cabinet and transmits the detected data to the processing module; The alarm module (7) receives the replacement warning signal transmitted by the processing module (3), then controls the warning light to issue sound and light alarm, and sends information to the staff through the transmission function of the module, reminding the staff to replace the power distribution cabinet.

6. A low voltage switchgear according to claim 1, characterized in that The steps of temperature and gas concentration data analysis of the processing module (3) are as follows: K1: A binary coordinate system is established with temperature data / gas concentration data and collection time, corresponding coordinate points are drawn in the coordinate system, lines are connected between adjacent coordinate points, the slope of the line is calculated, and the slopes of the temperature line and the gas concentration line are compared with the corresponding preset change threshold; K2: if the slope of the corresponding connection is greater than the preset variation threshold of the corresponding item, it is determined that there is a danger, and the danger level and is equal to the slope value of the corresponding item minus the preset variation threshold of the corresponding item, and divided by the preset variation threshold of the corresponding item; K3: If the slope of the corresponding connection is less than the preset change threshold of the corresponding item, record the detection data of the current corresponding item, and substitute the detection data before the time point into the formula , get and The specific value of is the detection data of the corresponding item, is the detection time; According to the formula, it can be judged that after the time , the detection data of the corresponding item will reach the preset warning threshold, if the preset reaction time , it is determined that there is danger, the danger level and is equal to the time of the corresponding item minus the preset reaction time of the corresponding item, and divided by the preset reaction time of the corresponding item.

7. A low voltage switchgear according to claim 6, characterized in that The steps of equipment health degree analysis of the processing module are as follows: M1: quantifying the equipment health degree of the power distribution cabinet according to the risk level, the equipment health degree , , , , and are weight coefficients of corresponding items respectively; when the equipment health degree is less than a preset equipment health degree threshold, it is determined that the safety hidden danger of continuing to use the equipment is large, a replacement warning signal is generated, and the replacement warning signal is transmitted to an alarm module (7); M2: retrieve historical failure information, count the occurrence times of the three abnormalities in the historical failure information, and then divide the corresponding occurrence times of the three abnormalities by the total number of occurrences of the three abnormalities to obtain the corresponding weight coefficients 、 and ; M3: Obtain the accuracy of the abnormality judgment of the two analysis methods of the number of changes and the gray value change, divide the accuracy corresponding to the analysis method by the sum of the accuracies of the two analysis methods, and obtain the corresponding weight coefficient and .

Images